Thermal conductivity prediction by atomistic simulation methods: Recent advances and detailed comparison

X Gu, Z Fan, H Bao - Journal of Applied Physics, 2021 - pubs.aip.org
Atomistic simulation methods, including anharmonic lattice dynamics combined with the
Boltzmann transport equation, equilibrium and non-equilibrium molecular dynamics …

A review of recent advances and applications of machine learning in tribology

AT Sose, SY Joshi, LK Kunche, F Wang… - Physical Chemistry …, 2023 - pubs.rsc.org
In tribology, a considerable number of computational and experimental approaches to
understand the interfacial characteristics of material surfaces in motion and tribological …

Extremely anisotropic van der Waals thermal conductors

SE Kim, F Mujid, A Rai, F Eriksson, J Suh, P Poddar… - Nature, 2021 - nature.com
The densification of integrated circuits requires thermal management strategies and high
thermal conductivity materials,–. Recent innovations include the development of materials …

GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations

Z Fan, Y Wang, P Ying, K Song, J Wang… - The Journal of …, 2022 - pubs.aip.org
We present our latest advancements of machine-learned potentials (MLPs) based on the
neuroevolution potential (NEP) framework introduced in Fan et al.[Phys. Rev. B 104, 104309 …

Neuroevolution machine learning potentials: Combining high accuracy and low cost in atomistic simulations and application to heat transport

Z Fan, Z Zeng, C Zhang, Y Wang, K Song, H Dong… - Physical Review B, 2021 - APS
We develop a neuroevolution-potential (NEP) framework for generating neural network-
based machine-learning potentials. They are trained using an evolutionary strategy for …

Tunable anisotropic thermal transport in porous carbon foams: The role of phonon coupling

XK Chen, XY Hu, P Jia, ZX **e, J Liu - International Journal of Mechanical …, 2021 - Elsevier
Carbon foams (CFs) possess high storage capacity, good electronic conductivity and superb
mechanical strength, which demonstrate promising applications in many engineering fields …

General-purpose machine-learned potential for 16 elemental metals and their alloys

K Song, R Zhao, J Liu, Y Wang, E Lindgren… - Nature …, 2024 - nature.com
Abstract Machine-learned potentials (MLPs) have exhibited remarkable accuracy, yet the
lack of general-purpose MLPs for a broad spectrum of elements and their alloys limits their …

Modeling heat transport in crystals and glasses from a unified lattice-dynamical approach

L Isaeva, G Barbalinardo, D Donadio… - Nature communications, 2019 - nature.com
We introduce a novel approach to model heat transport in solids, based on the Green-Kubo
theory of linear response. It naturally bridges the Boltzmann kinetic approach in crystals and …

Influence of thermostatting on nonequilibrium molecular dynamics simulations of heat conduction in solids

Z Li, S **ong, C Sievers, Y Hu, Z Fan, N Wei… - The Journal of …, 2019 - pubs.aip.org
Nonequilibrium molecular dynamics (NEMD) has been extensively used to study thermal
transport at various length scales in many materials. In this method, two local thermostats at …

Heat conduction theory including phonon coherence

Z Zhang, Y Guo, M Bescond, J Chen, M Nomura… - Physical Review Letters, 2022 - APS
Understanding and quantifying the fundamental physical property of coherence of thermal
excitations is a long-standing and general problem in physics. The conventional theory, ie …